Domain experts that can code are among the highest paid people in several industries. So, if you don't know how to code, it would likely be a valuable skill to

Domain experts that can code are among the highest paid people in several industries. So, if you don't know how to code, it would likely be a valuable skill to learn. Python is probably sufficient for many industries, though some of the performance-minded fields want C++ and even Fortran(!). Lots of scientific computing requires a lot of math and is used in many industries (a company I did contract work for in the past had contracts doing fluid dynamics for P&G, geological analysis for ConocoPhillips, and something for NASA...all using the same set of technical tools, specifically Python, NumPy/SciPy, and some C++/Fortran backend stuff for performance; the company was founded by a math PhD and they employed multiple math PhDs and at least half of the people they employed had some sort of significant math background). So, if I were in your shoes, I'd learn SciPy/NumPy, and start following the related communities for job postings. There's a lot of demand and a lot of good-paying positions surrounding those communities. Data science works with math, too, but not often at the advanced levels it sounds like you might be looking for. AI/ML is also somewhat mathy, but not as much as one might think (though I get the feeling there's room for more mathy approaches to problems that are currently very brute-forcey, but my understanding of math and of AI/ML is low enough to where that gut feeling could very well be wrong). Finally, digital signal processing is an area with significant reliance on math (though pretty specific sub-genres of math). I've recently started taking a couple of math MOOCs to refresh my memory of higher maths (and to learn it for the first time in some cases) so I can understand DSP algorithms for audio and music a little better. DSP has many applications in mobile devices, voice recognition, music and audio and video, etc.